5 citations · 18 across the 14 of their papers we have counts for
Showing 2024 · cs.CLShow all
2 papers · 2 filters
cs.CL2024★ 2 cited
MAP-Neo: Highly Capable and Transparent Bilingual Large Language Model Series
Ge Zhang, Scott Qu, Jiaheng Liu +42
Large Language Models (LLMs) have made great strides in recent years to achieve unprecedented performance across different tasks. However, due to commercial interest, the most comp…
cs.CL2024★ 5 cited
COIG-CQIA: Quality is All You Need for Chinese Instruction Fine-tuning
Yuelin Bai, Xinrun Du, Yiming Liang +19
Remarkable progress on English instruction tuning has facilitated the efficacy and reliability of large language models (LLMs). However, there remains a noticeable gap in instructi…